Pfizer has 19 active AI-related job listings. The majority of these roles are focused on agents, accounting for 32% of the openings, followed by data roles at 26%. Engineering is the most frequent function, with 14 positions. The company is actively hiring for roles involving agent orchestration, model serving, and RAG. Over the last 30 days, Pfizer posted 45 new AI roles.
Currently tracking 10 active AI roles, down 57% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$358k (avg $176k).
Pfizer currently has 18 active AI-related roles in our index. The most common open titles are: Clinical Development Scientist, Director (Inflammation and Immunology) (2), AI Data Engineer--LLMs / Agentic Systems, AI/ML Engineer - Vaccine Research, Business Title Senior Scientist, Sterile Injectables Design, Director of AI Engineering – Vaccine R&D Operations Enablement. Most positions are in Engineering and Product.
Pfizer's active AI hiring is concentrated in: application (44%), agents (28%), post-training (11%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Pfizer is hiring AI talent in: United States (13 roles), China (2 roles), Spain (1 role), India (1 role).
Job postings at Pfizer most frequently reference: llm observability, model serving, rag, agent orchestration, fine tuning.
In the past 30 days, Pfizer has posted 24 new AI-related roles. That is a -27% change versus the prior 30 days (33 → 24).
| Title | Stage | AI score |
|---|---|---|
| Senior Director, Applied AI - US Commercial Senior Director, Applied AI role focused on enterprise strategy, system-level architecture, and leading teams to deliver AI solutions at scale. The role requires shaping AI strategy, designing operating models, and ensuring coherence across initiatives, with a hands-on technical component in modern AI and agent frameworks. It emphasizes translating technological possibilities into business value and maintaining quality and security standards. | AgentServe | 8 |
| Director, AI Solutions Expert—Agent Developer, AIA Lead the design, development, and deployment of AI agents for enterprise workflow automation, decision enhancement, and intelligent user interactions, focusing on multi-agent frameworks, scalability, ethics, and performance. This role involves architectural design, implementation using cloud infrastructure and MLOps, and operational excellence with a focus on collaboration and innovation. |
| Agent |
| 8 |
| PharmSci Agentic and Generative AI Architect This role is for a hands-on technical leader responsible for designing, building, and scaling agentic and generative AI solutions in the pharmaceutical sciences. The architect will translate ideas into production-ready AI systems, focusing on agentic AI systems with multi-step reasoning and tool use, as well as enterprise-grade GenAI solutions including RAG, orchestration, and evaluation. They will lead pilots, scale solutions, establish architectural patterns, ensure reliability and performance, integrate with existing systems, and mentor team members. Responsible AI practices, governance, security, and monitoring are also key aspects of the role. | Agent | 8 |
| Director, AI Engineering--Clinical Development and Operations (CD&O) This role focuses on designing, building, and deploying production-grade AI systems, particularly LLMs and agentic AI, for clinical development and operations within a regulated healthcare environment. It involves developing predictive models, engineering robust ML pipelines, and implementing agentic solutions, with a strong emphasis on MLOps and cloud deployment. | AgentServe | 8 |
| AI Data Engineer--LLMs / Agentic Systems This role focuses on building and deploying production-grade full-stack applications that integrate LLM and AI capabilities into pharmaceutical research workflows. Responsibilities include developing backend services for data processing, embedding generation, vector search, and LLM orchestration, creating frontend interfaces, implementing RAG systems and agentic LLM architectures, and deploying/maintaining systems on AWS. The role also involves contributing to semantic frameworks and conceptual research. | AgentData | 7 |